Image denoising of coal dust based on fractional calculus adaptive algorithm

Abstract

In view of problem of long iteration process, unsatisfactory image denoising effect and poor texture retention capacity of traditional denoising method of coal dust image, the paper improved existing method and built an adaptive denoising algorithm based on fractional calculus model. The improved algorithm adjusts gradient of fractional order u from integer order to fractional order, and makes model parameters vary adaptively according to regional characteristics. The experimental results show that the improved denoising algorithm has fast convergence, fewer iterations, good denoising effect, and strong texture retention ability, while its quantitative indicators to measure noise effect are improved.

Keywords

• coal dust
• image denoising
• fractional calculus adaptive algorithm
• psnr
• epi